AdvScripts/Example_MS_Regress_Simul_Fit_2_States_dist_t.r

# Example script for MS_Regress_Simul and MS_Regress_Fit (2 states, t distribution)
# The script will first simulate a markov switching process given the input and then fit it using MS_Regress_Fit

library(fMarkovSwitching)   # Assuming library is installed

nr=200
distrib<-"t"
k<-2

PVec<-rbind(c(.9 ,.2),
            c(.1 ,.8)) 
        
P<-matrix(PVec,k,k)
S<-c(1,0,0)
nS_param<-matrix(c(.5,-.2),2,1)    # Setting up the coefficients at non switching parameters
S_param<-matrix(0,sum(S),k)
S_param[,1]= .2                    # Setting up the coefficients at switching parameters
S_param[,2]=-.3

sigma<-matrix(0,1,k)
sigma[1,1]=.02               # Setting up the standard deviavion of the model at State 1
sigma[1,2]=.01               # Setting up the standard deviavion of the model at State 2

v<-matrix(0,1,k)
v[1,1]=10               # Setting up the degree of freedom (t distribution parameter) of the model at State 1
v[1,2]=5                # Setting up the degree of freedom (t distribution parameter) of the model at State 2

Coeff<-list(P=P               ,
            S=S               ,
            nS_param=nS_param ,
            S_param=S_param   ,
            sigma=sigma       ,
            v=v)

mySimul<-MS_Regress_Simul(nr,Coeff,k,distrib)

print(mySimul)
plot(mySimul)

dep<-mySimul@dep
indep<-mySimul@indep

myModel<-MS_Regress_Fit(dep,indep,S,k,distrib)
print(myModel)
plot(myModel)

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fMarkovSwitching documentation built on May 2, 2019, 5:58 p.m.